Untitled

defaultEncoding <- "UTF8"
library(dplyr)
library(sf)
library(terra)
library(raster)
library(DT)
library(ggplot2)
library(plotly)
library(leaflet)

casos <-
  st_read(
    "/vsicurl/https://marcelocubero.github.io/capas_proyecto/casos.geojson",
    quiet = TRUE
  )
casos <-
  casos %>%
  st_transform(4326)

casos_ <-
    read.csv( file= "https://marcelocubero.github.io/capas_proyecto/casos_.csv",
              sep = ",", encoding = "UTF-8") 


fallecidos <- rast("/vsicurl/https://marcelocubero.github.io/capas_proyecto/fallecidos.tif")

fallecidos_rl <- raster::raster(fallecidos)


leaflet() %>%
  addTiles(group="OSM") %>% 
  addProviderTiles(providers$Esri.NatGeoWorldMap , group="NatGeo") %>% 
  addProviderTiles(providers$CartoDB.DarkMatter, group="CartoDB-Black") %>%
  addRasterImage(
    fallecidos_rl, 
    opacity = 0.7,
    group= "Fallecidos",
  ) %>%
  addPolygons(
    data = casos,
    color = "black",
    fillColor = "transparent",
    stroke = TRUE,
    weight = 1.0,
    group= "Casos"
  )  %>%
  addLayersControl(
    baseGroups = c("OSM", "NatGeo", "CartoDB-Black"),
    overlayGroups = c("Fallecidos", "Casos"),
    options = layersControlOptions(collapsed = FALSE)
  ) 

casos_ %>%
  select(Cantón= canton,Provincia= provincia, Casos_Activos= activos, Casos_Positivos= positivos) %>%
datatable( casos_, options = list(
  language = list(url = '//cdn.datatables.net/plug-ins/1.10.11/i18n/Spanish.json'),
  pageLength = 5
))

ggplot(casos_, aes(x= canton, y= positivos)) +
  geom_col( width = 0.5, fill= "#008080") +
  ggtitle("Casos Positivos por cantón") +
  xlab("Cantón") +
  ylab("Cantidad de casos positivos") +
   theme(
    plot.title = element_text(size = 16, face = "bold"),
    text = element_text(size=8),
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)
  ) 

ggplot(casos_, aes(x= canton, y= activos)) +
  geom_col( width = 0.5, fill= "#00FF7F") +
  ggtitle("Casos Activos por cantón") +
  xlab("Cantón") +
  ylab("Cantidad de casos activos") +
   theme(
    plot.title = element_text(size = 16, face = "bold"),
    text = element_text(size=8),
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)
  )